Economic Aspects of Greenhouse Gas Emissions Reduction by Utilisation of Wind and Solar Energies to Produce Electricity and hydrogen
Bibliographic record
Abstract
Implementation of renewable wind and solar energy sources instead of fossil fuels to produce such energy carriers as electricity and hydrogen facilitates reductions in gaseous emissions. Unlike for traditional fossil fuel technologies, greenhouse gas emissions from renewable technologies are associated mainly with the construction of a power plant. With present costs of wind and solar electricity, it is shown that, when electricity from renewable sources replaces electricity from natural gas, the cost of greenhouse gas emissions abatement is about four times less than the cost if hydrogen from renewable sources replaces hydrogen produced from natural gas. When renewable-based hydrogen is used instead of gasoline in a fuel cell vehicle, the cost of greenhouse gas emissions reduction approaches the same value as for renewable-based electricity only if the fuel cell vehicle efficiency exceeds significantly (i.e., by about two times) that of an internal combustion vehicle. It is also shown that when 6000 turbines (Kenetech KVS-33) with a capacity 350 kW and a capacity factor of 24% replace a 500-MW gas-fired power generation plant with an efficiency of 40%, annual greenhouse gas emissions are reduced by 2.3 megatons. The incremental additional annual cost is about $280 million (US). The results provide a useful approach to an optimal strategy for greenhouse gas emissions mitigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".